From Wi-Fi to Warcraft : End-to-End Enhancements for Seamless Mobile Applications

1. From Wi-Fi to Warcraft:End-to-End Enhancements for Seamless Mobile Applications Justin Manweiler Duke University

2. Four Grand Challenges in Mobile Computing Power Redesigning for Energy Efficiency “Why is my battery dead, already?” (Wireless Network) Performance Capacity, Robustness, Management Privacy For Locations, Interactions, Behaviors, Not everyone wants to be called “Mayor.” Pervasiveness Adapting to Humans and Surroundings The “smart” in smartphone. Today’s talk will instantiate each through a system design

3. Perspective • Well-known problems in mobile/wireless space • Despite clear problems, ubiquitous use • Now beyond early adopters, need seamlessness My research considers the end-to-end experience, from communication to application

4. Approach • Bottom-up and Top-down • New primitives to solve near-at-hand problems • Interdisciplinary • Convergence of many domains, technologies, techniques • Empirical • Real-world pitfalls; don’t want to abstract away complexity • Practical • Standards-compliant, off-the-shelf hardware, deployable

5. Challenging Contexts Enterprise Home On-the-Go Performance “Plug-and-play” Simplicity Scarce Resources Dynamic Environments, Adaptation Privacy Reliability SleepWell Surveyor SMILE Shuffle RxIP Switchboard BytesToGo

6. Today’s Talk: 2 Parts Top-down Bottom-up SleepWell MobiSys 2011Best Paper Nominee Runner-up Best Demo (in depth) Switchboard MobiSys 2011 SMILE CCS 2009 Surveyor Ongoing

8. : Saving Energy through Sleep WiFi Between packet bursts, WiFiswitches to low-power sleep mode Zzz… Zzz… Time

9. WiFiSleep Under Contention Zzz… Zzz… Zzz… Zzz… Time Time

10. Beacon Wakeups Bad wakeups = burst contention Traffic Download Key intuition: move beacons, spread apart traffic, let clients sleep faster

11. vs Measurements Energy performance on modern WiFi smartphones Zzz… Zzz…

12. Measuring Power on Nexus One Simultaneous measurements at 5K hertz

13. Energy Profile of Nexus One Transmit/Receive Beacon Wakeups Idle/Overhear Deep Sleep Light Sleep With contention: ↑Idle/Overhear,↓Sleep

14. Energy Cost of Contention Energy costs grow with number of contenders File Download Denser Neighborhood

15. Activity Percentages Increasing time in Idle/Overhear Time Transmit/Receive

16. Seattle 520 bridge Wakeup later / go home later Smarter commute = save gas Smarter beacons = save battery SleepWell Design Avoiding the rush hours to save energy

17. SleepWellTechniques • Traffic Monitoring • APs maintain a map of peers in the wireless vicinity • Traffic Migration • APs select a new beacon position based on heuristics • Traffic Preemption • APs avoid traffic spillover into that of neighbors

18. Traffic Monitoring beacon & traffic maps for the one-hop neighborhood

19. Traffic Migration 0 85 Expected share= 100/(n + 1) = 25 ms 25 75 Claim expected share from largest hole 70 CONVERGES 55 55 50

20. Traffic Preemption 0 25 75 Traffic preemptionprevents spillover 50

21. Key Implementation Challenge • APs need to change the beacon timings • But, no 802.11 protocol support • Fortunately, clients synchronize to AP clocks • AP can change beacon by “lying” about the time 40 Fully 802.11 compatible AP: Hostapd + modified Atheros Ath9k 802.11n driver

22. Rescheduling Client Wakeups • I know client will • wakeup in 40ms • OK, I need to • wakeup in 40ms • Yes, delayed • client by 40ms • Right • on time • I’ll adjust • my clock • “hey client • this beacon is • 60ms Late” 0 0 Actual Time Client Clock (sync to AP) 50 50

23. Energy TDMA

24. Energy Comparison File Download

25. Activity Percentages: 802.11 Transmit/Receive

26. Activity Percentages: SleepWell Transmit/Receive

27. Youtube CDF, Instantaneous Power SleepWell closely matcheszero-contention energy profile

28. Throughput under SleepWell(per-link TCP on 4 AP testbed) Negligible performance impact: SleepWell just reorders traffic

29. SleepWellTake-away • PSM is a valuable energy-saving optimization • But, PSM designed with a single AP in mind • Multiple APs induce contention, waste energy • Staggered wakeups  clients sleep through contention • SleepWell = PSM made efficient for high-density networks to Zzz… Zzz…

30. Today’s Talk: 2 Parts Top-down Bottom-up SleepWell MobiSys 2011Best Paper Nominee Runner-up Best Demo (in depth) Switchboard MobiSys 2011 SMILE CCS 2009 Surveyor Ongoing

31. Time Spent on Mobile Apps Other Entertainment News Gaming Social Networking Flurry Analytics, May 2011

32. Switchboard A Matchmaking System for Multiplayer Mobile Games Other Entertainment News Gaming Social Networking

33. Mobile Games: Now and Tomorrow Increasing Interactivity Single-player Mobile (mobile today) Multiplayer Turn-based (mobile today) Multiplayer Fast-action (mobile soon)

34. Key Challenge Bandwidth is fine:250 kbps to host 16-player Halo 3 game Delay bounds are much tighter Challenge: find groups of peers than can play well together

35. The MatchmakingProblem Estimate 3G Link Performance Cluster Users to Assign Groups Design for Scalability

36. 3G Latency is Unstable Due to instability, must consider latency distribution

37. “Black Box” Latency Estimation IP network Internet GGSN GGSN “Black Box” SGSN SGSN RNC RNC End-to-end Performance Crowdsourced Measurement

38. Crowdsourcing 3G over Time Latency Similarity by Time Time

39. Crowdsourcing 3G over Space Latency Similarity by Distance

40. One Result: Stability over Space Similarity at the same cell tower Substantial variation Divergence between nearby towers Takeaway: Scalable Measurement through Reuse

41. SMILE Encounter-based Trust for Mobile Social Services Other Entertainment News Gaming Social Networking

42. Mobile Social Services • How can Alice contact Bob? • “Missed Connections” problem • Cute example, but really? • Anonymous support groups • Retrieve left-behind items • Discussion after a seminar • Lost phone number • Sharing photos • …

43. Low-tech: Craigslist craigslist Bay Area listings “We saw each other on the subway…” Completely Impractical Alice Bob Bob “Hi, I’m Bob!”

44. Naïve Mobile Missed Connections Impersonation Leaked/Stolen Data Service Provider Internal Abuse Alice @ {Subway, 1:00 PM} Bob @ {Subway, 1:00 PM} Trustworthy? Snooping, De-anonymization “Remember me?”

45. High-level Approach • Create “shared knowledge” of encounter • Peers establish cryptographically-secure secrets • Secret never revealed to any third party

46. Sharing Keys with Bluetooth Encounter Key KeyAB = KeyA⊕ KeyB KeyA Encounter Key KeyAB = KeyA⊕ KeyB KeyB Keys create shared knowledge only known to co-located devices

47. Keys and Key Hashes Service Provider Unique match, obvious encounter Bob @ H(KAB); {“Hi…”}KAB Bob @ H(KAB) Alice @ H(KAB); {“Hi…”}KAB Alice @ H(KAB) Protects location privacy End-to-end secure channel What about encounter privacy?

48. Key-hash Collisions Alice @ Pre(H(KAB)); {“Hi…”}KAB Only Bob can decrypt Chris @ Pre(H(KCD)) Dave @ Pre(H(KCD)) Bob @ Pre(H(KAB)) Alice @ Pre(H(KAB)) Service Provider ? Users reveal only Prefix[KeyHash] Pre(H(KAB)) =Pre(H(KCD))

49. SMILE Take-away • Trading communication overhead for privacy • Users choose k-anonymity through prefix length • Decentralization of the root-of-trust • End-to-end channel, with locations/encounters protected • Usage assumptions that match the real world • Validated by reading many Craigslist posts

50. Surveyor Object Localization for the the Visible Vicinity Other Entertainment News Gaming Social Networking